# Disponivel no pacote de programas como: dataaug.py
#Data Augmentation Algorithm
from numpy.random import *
import random as rn
from pylab import *

#prior of theta is assumed to be uniform
th  = uniform(0,1,10000)
for i in xrange(10000):
    x = binomial(125,th[i])
    
# post = p(th|Y)
#post = mean(betavariate(,))
